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Open Access Research article

Missing the boat: odds for the patients who leave ED without being seen

Jabeen Fayyaz*, Munawar Khursheed, Mohammed Umer Mir and Amber Mehmood

Author Affiliations

Department of Emergency Medicine, Aga Khan University Hospital, Karachi, Pakistan

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BMC Emergency Medicine 2013, 13:1  doi:10.1186/1471-227X-13-1

Published: 16 January 2013

Abstract

Background

A patient left without being seen is a well-recognized indicator of Emergency Department overcrowding. The aim of this study was to define the characteristics of LWBS patients, their rates and associated factors from a tertiary care hospital of Pakistan.

Methods

A retrospective patient record review was undertaken. All patients presenting to the Aga Khan University Hospital, Karachi, between April and December of the year 2010, were included in the study. Information was collected on age, sex, presenting complaints, ED capacity, month, time, shift, day of the week, and waiting times in the ED. A basic descriptive analysis was made and the rates of LWBS patients were determined among the patient subgroups. Logistic regression analysis was used to assess the risk factors associated with a patient not being seen in the ED.

Results

A total of 38,762 patients visited ED during the study period. Among them 5,086 (13%) patients left without being seen. Percentage of leaving was highest in the night shift (20%). The percentage was twice as high when the ED was on diversion (19.8%) compared to regular periods of operation (9.8%). Mean waiting time before leaving the ED in pediatric patients was 154 minutes while for adults it was 171 minutes. More than 32% of patients had waited for more than 180 minutes before they left without being seen, compared to the patients who were seen in ED. Important predictors for LWBS included; Triage category P4 i.e. walk –in-patients had an OR of 13.62(8.72-21.3), Diversion status, OR 1.49(1.26-1.76), night shift , OR 2.44(1.95-3.05) and Pediatric age, OR 0.57(0.48-0.66).

Conclusions

Our study elucidates the LWBS population characteristics and identifies the risk factors for this phenomenon. Targeted interventions should be planned and implemented to decrease the waiting time and alternate services should be provided for high-risk patients (for LWBS) to minimize their number.